Microwave Disinfection: Assessing the Risks of Irrigation Bottle and Fluid Contamination
Bibliographic record
Abstract
BACKGROUND: It was previously shown that 50% of irrigation bottles and 40% of irrigation fluids had evidence of bacterial contamination despite cleaning with hot water and soap. Although a novel method of microwave disinfection has recently been proposed to minimize contamination risk, this has not been studied in a real life setting. This study investigates the effectiveness of microwave disinfection for reducing both nasal irrigation bottle and irrigation fluid contamination risk after endoscopic sinus surgery (ESS). METHODS: Twenty consecutive patients underwent ESS for chronic rhinosinusitis. Patients were given NeilMed Sinus Rinse bottles (NeilMed Pharmaceuticals, Inc., Santa Rosa CA) to use twice daily, with microwave cleaning instructions preoperatively. Bottles were collected and cultured 1 week postoperatively. Sterile saline (5 mL) was mixed into the irrigation bottle and cultured separately. An additional 10 patients were recruited whereby the bottle was cultured at collection and immediately after microwave disinfection was performed in the clinic. RESULTS: For the first cohort of the study, 40% of the bottles and 20% of the irrigation samples had positive cultures 1 week postoperatively. Common bacteria included Acinetobacter, coagulase-negative Staphylococcus, and Gram-negative bacilli. For the second cohort of patients, 20% of the irrigation bottles had positive cultures. However, after supervised microwave disinfection, there was a 0% contamination rate. CONCLUSION: Despite detailed instructions on microwave disinfection, positive bacterial cultures may still occur after ESS. This risk, however, appears to be significantly reduced when bottles are microwaved under supervision. These findings suggest either a reduced patient compliance to cleaning or a time-dependent recontamination risk after disinfection.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".